Gangyi Yang

8.1k citations
237 papers · 6.0k indexed · h-index 44

Impact in

Papers in

Gangyi Yang

232 papers receiving 5.9k citations

Peers

Gangyi Yang
Comparison fields: 5 of 170
  • Endocrine and Autonomic Systems 514
  • Endocrinology, Diabetes and Metabolism 1.3k
  • Physiology 1.4k
  • Epidemiology 1.4k
  • Rehabilitation 228
Replace Wei‐Shiung Yang with:
Wei‐Shiung Yang Taiwan
Francesco Bèguinot Italy
In‐Kyu Lee South Korea
Pietro Formisano Italy
Esma R. Isenović Serbia
Shen Qu China
Luigi Laviola Italy
Joong‐Yeol Park South Korea
Claudia Miele Italy
John Beilby Australia
Gangyi Yang relative to Wei‐Shiung Yang Taiwan Wei‐Shiung Yang's profile →
Citations per field
00.5×1.5×2.3×
Wei‐Shiung Yang · 1×
Citations per year

Countries citing papers authored by Gangyi Yang

Since Specialization
Citations

This map shows the geographic impact of Gangyi Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gangyi Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gangyi Yang more than expected).

Fields of papers citing papers by Gangyi Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gangyi Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gangyi Yang. The network helps show where Gangyi Yang may publish in the future.

Co-authors

The 25 scholars most cited alongside Gangyi Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gangyi Yang Line = papers co-authored together Gangyi Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20253
2 20251
3 20245
4 202410
5 20243
6 20236
7 20237
8
Construction and Validation of a Prediction Model for Identifying Clinical Risk Factors of Lateral Lymph Node Metastasis in Medullary Thyroid Carcinoma
20223
9 20227
10 202214
11 20228
12 202111
13 20202
14 20193
15 20159
16 201319
17 20129
18 201148
19 200854
20 20081

About Gangyi Yang

Gangyi Yang is a scholar working on Endocrinology, Diabetes and Metabolism, Endocrine and Autonomic Systems, Physiology, Epidemiology and Reproductive Medicine, having authored 237 papers that have together received 6.0k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (40 papers), Adipokines, Inflammation, and Metabolic Diseases (39 papers), Metabolism, Diabetes, and Cancer (36 papers), Diabetes Treatment and Management (26 papers), Regulation of Appetite and Obesity (24 papers), Lipid metabolism and disorders (21 papers), Liver Disease Diagnosis and Treatment (19 papers) and Pancreatic function and diabetes (17 papers). The work is most often cited by research in Endocrine and Autonomic Systems (514 citations), Endocrinology, Diabetes and Metabolism (1.3k citations), Physiology (1.4k citations), Epidemiology (1.4k citations) and Rehabilitation (228 citations). Gangyi Yang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ling Li, Mengliu Yang, Hua Liu, Guenther Boden, Dongfang Liu, Hongting Zheng, Zhiming Zhu, Yi Tang, L. Li and Shengbing Li. Their work appears in journals such as Diabetes, Cytokine, Diabetes Obesity and Metabolism, Metabolism and Frontiers in Endocrinology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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